Aiming at the path planning problem of mobile robots in a large range of unstructured scenes, this paper proposes a Jump A*(JA*) path planning algorithm based on a hierarchical grid map, which combines the improved jump point search(JPS) algorithm with A* search. In this algorithm, the 3D point cloud map is rasterized and stratified, and the environmental information is divided into a structural layer and a non-structural layer. In addition, the search strategy switching rules are established, and different search strategies are used according to the layer information, so as to effectively reduce the computational cost. In order to verify the effectiveness of the JA* algorithm, simulation is carried out in 3D maps with different layer proportions. Simulation results show that compared with the traditional A* algorithm, the JA* algorithm traverses fewer nodes, has higher search efficiency, and has higher robustness compared with the bidirectional A* algorithm. Finally, the JA* algorithm is applied to the public data set, and the experimental results show that the JA* algorithm can effectively solve the path planning problem of a mobile robot in a large range of unstructured scenarios.